
import osmnx as ox
import numpy as np
import pandas as pd
import geopandas as gp
import folium


region1 = "Costa Rica"
etiqueta1 = {'amenity':"bank"}
resultado1 = ox.geometries_from_place(query = region1, tags = etiqueta1)
display(resultado1.columns)

Index(['unique_id', 'osmid', 'element_type', 'amenity', 'name', 'geometry',
       'addr:city', 'addr:street', 'atm', 'phone', 'name:es', 'nodes', 'brand',
       'brand:en', 'brand:es', 'brand:wikidata', 'brand:wikipedia', 'building',
       'name:en', 'official_name', 'official_name:en', 'official_name:es',
       'short_name', 'source', 'drive_through', 'opening_hours', 'operator',
       'website', 'addr:full', 'area', 'alt_name', 'level', 'note',
       'addr:postcode', 'building:levels', 'construction', 'fixme',
       'designation', 'fee', 'name:de', 'ele', 'addr:housename', 'int_name',
       'wheelchair', 'name:it', 'source_1', 'operator:wikidata',
       'operator:wikipedia', 'addr:place', 'indoor', 'addr:local', 'parts',
       'email', 'buildingpart', 'height', 'phone_1', 'phone_2', 'ways', 'type',
       'is_in', 'addr:suburb', 'description', 'addr:housenumber', 'landuse',
       'cajero', 'shop', 'building:colour', 'roof:colour', 'air_conditioning',
       'amenity_1', 'alt_name:en', 'alt_name:es', 'highway'],
      dtype='object')


bancos = resultado1[["name","geometry"]]
bancos = bancos.dropna()
bancosbn = bancos[bancos.name.str.match('^Banco Nacional')]
bancosbcr = bancos[bancos.name.str.match('^Banco de Costa')]
bancosbac = bancos[bancos.name.str.match('^BAC')]
bancosbp = bancos[bancos.name.str.match('^Banco Popular')]
coord1 = pd.concat([bancosbn,bancosbcr,bancosbac,bancosbp])
points1 = coord1[[True if geometry.__class__.__name__ == "Point" else False for geometry in coord1.geometry]]
points1 [["name","geometry"]].head(17)
points1 ['x'] = points1['geometry'].x
points1 ['y'] = points1['geometry'].y
points1 [["name", "x","y"]].head(15)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\geopandas\geodataframe.py:1322: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  super(GeoDataFrame, self).__setitem__(key, value)


polygon1= coord1[[True if geometry.__class__.__name__ == "Polygon" else False for geometry in coord1.geometry]]
polygon1[["name","geometry"]].head(15)
polygon1["x"] = polygon1.centroid.x
polygon1["y"] = polygon1.centroid.y
polygon1[["name", "x","y"]].head(15)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  This is separate from the ipykernel package so we can avoid doing imports until
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\geopandas\geodataframe.py:1322: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  super(GeoDataFrame, self).__setitem__(key, value)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:4: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  after removing the cwd from sys.path.


resultado2 = points1.append(polygon1)
resultado2 = resultado2[["name","x","y","geometry"]]
resultado2[["name", "x","y"]].head(15)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


m = folium.Map(location=[9.934598, -84.094154], zoom_start = 13)
folium.TileLayer('CartoDB positron').add_to(m)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

<folium.raster_layers.TileLayer at 0x1f003f3dec8>


estilos1 = {"Banco Nacional":{"color":"blue"},"Banco Popular":{"color":"orange"}, "BAC":{"color":"red"}, "Banco de Costa Rica": {"color":"green"}}


for banco in resultado2.itertuples():
    if banco.name == 'Banco Nacional':
        esti = estilos1["Banco Nacional"]
    elif banco.name == 'BAC':
        esti = estilos1["BAC"]
    elif banco.name == 'Banco Popular':
        esti = estilos1["Banco Popular"]
    elif banco.name == 'Banco de Costa Rica':
        esti = estilos1["Banco de Costa Rica"]
    c = folium.Marker(location=[banco.y, banco.x], popup = banco.name,
                    icon = folium.Icon(color = esti["color"],
                    icon_color = 'white')).add_to(m)

m


import folium.plugins
n = folium.Map(location=[9.934598, -84.094154], zoom_start = 13)
folium.TileLayer('CartoDB positron').add_to(n)

<folium.raster_layers.TileLayer at 0x1f006355648>


cluster = folium.plugins.MarkerCluster().add_to(n)
for banco in resultado2.itertuples():
    if banco.name == 'Banco Nacional':
        esti = estilos1["Banco Nacional"]
    elif banco.name == 'BAC':
        esti = estilos1["BAC"]
    elif banco.name == 'Banco Popular':
        esti = estilos1["Banco Popular"]
    elif banco.name == 'Banco de Costa Rica':
        esti = estilos1["Banco de Costa Rica"]
    d = folium.Marker(location=[banco.y, banco.x], popup = banco.name,
                    icon = folium.Icon(color = esti["color"],
                    icon_color = 'white')).add_to(cluster)

n


import geopandas as gp
import os

pasada = os.getcwd()
os.chdir("C:/Users/rzamoram/OneDrive - Intel Corporation/Documents/Machine Learning/Visualizacion de Datos en Python/Semana 3")
print(os.getcwd())

datos_covid = pd.read_excel(io = "base-de-datos-IPS-cantonal.xlsx", sheet_name= "Datos")
datos_covid.head(15)

C:\Users\rzamoram\OneDrive - Intel Corporation\Documents\Machine Learning\Visualizacion de Datos en Python\Semana 3

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\openpyxl\worksheet\_reader.py:312: UserWarning: Unknown extension is not supported and will be removed
  warn(msg)


datos_covid = pd.melt(datos_covid,
id_vars = ['cve',"canton"],
var_name = 'oportunidades',
value_name = 'ips')

datos_covid.head(10)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\IPython\core\interactiveshell.py:3437: FutureWarning: This dataframe has a column name that matches the 'value_name' column name of the resulting Dataframe. In the future this will raise an error, please set the 'value_name' parameter of DataFrame.melt to a unique name.
  exec(code_obj, self.user_global_ns, self.user_ns)


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones.head()

#san_jose = cantones[cantones.provincia == "Cartago"]
#san_jose.head(5)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones = cantones.set_index('canton')
cantones.head(10)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


import re

def eliminar_tildes(texto):
        texto = re.sub('á','a', texto)
        texto = re.sub('é','e', texto)
        texto = re.sub('í','i', texto)
        texto = re.sub('ó','o', texto)
        texto = re.sub('ú','u', texto)
        texto = re.sub('ñ','n', texto)
        return texto.upper()

def arreglar_cantones(texto):
    texto = eliminar_tildes(texto)
    texto = re.sub('LEON CORTES CASTRO','LEON CORTES', texto)
    texto = re.sub('VAZQUEZ DE CORONADO','VASQUEZ DE CORONADO', texto)
    texto = re.sub('VALVERDE VEGA','SARCHI', texto)
    return texto

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones.index = [arreglar_cantones(x) for x in cantones.index]
cantones.head()


datos_covid.index = [arreglar_cantones(x) for x in datos_covid.canton]
datos_covid.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


set(cantones.index) - set(datos_covid.index)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

{'CANAS', 'RIO CUARTO'}


df = cantones.merge(delitos_mes_canton, left_on = "canton", right_index=True)
df.head(15)


df = cantones.merge(datos_covid,how = "left",
left_index = True,
right_index = True)
df.head(15)


df.ips

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

ABANGARES    85.280540
ABANGARES    95.038378
ABANGARES    69.104107
ABANGARES    87.244399
ABANGARES    83.601755
               ...    
ZARCERO      26.500000
ZARCERO       7.142857
ZARCERO      17.326789
ZARCERO       8.399566
ZARCERO       2.007853
Name: ips, Length: 4962, dtype: float64


x = df.centroid.x.mean()
print(x)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.

-84.22688272122


y = df.centroid.y.mean()
print(y)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.

9.955756377280855


import folium

x = df.centroid.x.mean()
y = df.centroid.y.mean()

m = folium.Map(location=[y, x], zoom_start = 9, tiles = None)
folium.TileLayer('CartoDB positron',control=False).add_to(m)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  This is separate from the ipykernel package so we can avoid doing imports until
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:4: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  after removing the cwd from sys.path.

<folium.raster_layers.TileLayer at 0x1f008785188>


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones.head()

cantones = cantones[cantones.provincia == "Cartago"]
cantones.head(5)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones = cantones.set_index('canton')
cantones.head(10)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones.index = [arreglar_cantones(x) for x in cantones.index]
cantones.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


datos_covid.index = [arreglar_cantones(x) for x in datos_covid.canton]
datos_covid.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


set(cantones.index) - set(datos_covid.index)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

set()


df = cantones.merge(datos_covid,how = "left",
left_index = True,
right_index = True)
df.head(15)


x = df.centroid.x.mean()
print(x)

-83.81587522794443

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.


y = df.centroid.y.mean()
print(y)

9.845582134363136

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.


import folium

x = df.centroid.x.mean()
y = df.centroid.y.mean()

m = folium.Map(location=[y, x], zoom_start = 9, tiles = None)
folium.TileLayer('CartoDB positron',control=False).add_to(m)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  This is separate from the ipykernel package so we can avoid doing imports until
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:4: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  after removing the cwd from sys.path.

<folium.raster_layers.TileLayer at 0x1f00adeba08>


choropleth = folium.Choropleth(
 geo_data = df,
 data = df,
 columns = ["canton","ips"],
 key_on = "feature.properties.canton",
 fill_color = 'OrRd',
 highlight = True).add_to(m)

m


import geopandas as gp
import os

pasada = os.getcwd()
os.chdir("C:/Users/rzamoram/OneDrive - Intel Corporation/Documents/Machine Learning/Visualizacion de Datos en Python/Semana 3")
print(os.getcwd())

datos_covid = pd.read_excel(io = "base-de-datos-IPS-cantonal.xlsx", sheet_name= "Datos")
datos_covid.head(15)

C:\Users\rzamoram\OneDrive - Intel Corporation\Documents\Machine Learning\Visualizacion de Datos en Python\Semana 3

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\openpyxl\worksheet\_reader.py:312: UserWarning: Unknown extension is not supported and will be removed
  warn(msg)


datos_covid = pd.melt(datos_covid,
id_vars = ['cve',"canton"],
var_name = 'oportunidades',
value_name = 'Vivienda')

datos_covid.head(10)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\IPython\core\interactiveshell.py:3437: FutureWarning: This dataframe has a column name that matches the 'value_name' column name of the resulting Dataframe. In the future this will raise an error, please set the 'value_name' parameter of DataFrame.melt to a unique name.
  exec(code_obj, self.user_global_ns, self.user_ns)


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones.head()

#san_jose = cantones[cantones.provincia == "Cartago"]
#san_jose.head(5)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones.head()

cantones = cantones[cantones.provincia == "Cartago"]
cantones.head(5)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones = cantones.set_index('canton')
cantones.head(10)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones.index = [arreglar_cantones(x) for x in cantones.index]
cantones.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


datos_covid.index = [arreglar_cantones(x) for x in datos_covid.canton]
datos_covid.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


set(cantones.index) - set(datos_covid.index)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

{'CANAS', 'RIO CUARTO'}


df = cantones.merge(datos_covid,how = "left",
left_index = True,
right_index = True)
df.head(15)


df.Vivienda

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

ABANGARES    85.280540
ABANGARES    95.038378
ABANGARES    69.104107
ABANGARES    87.244399
ABANGARES    83.601755
               ...    
ZARCERO      26.500000
ZARCERO       7.142857
ZARCERO      17.326789
ZARCERO       8.399566
ZARCERO       2.007853
Name: Vivienda, Length: 4962, dtype: float64


x = df.centroid.x.mean()
print(x)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.

-84.22688272122


y = df.centroid.y.mean()
print(y)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.

9.955756377280855


import folium

x = df.centroid.x.mean()
y = df.centroid.y.mean()

m = folium.Map(location=[y, x], zoom_start = 9, tiles = None)
folium.TileLayer('CartoDB positron',control=False).add_to(m)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  This is separate from the ipykernel package so we can avoid doing imports until
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:4: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  after removing the cwd from sys.path.

<folium.raster_layers.TileLayer at 0x1f0211f5988>


cantones = gp.read_file("geo_data/cantones/cantones.shp")
cantones.head()

cantones = cantones[cantones.provincia == "Cartago"]
cantones.head(5)


cantones = cantones.set_index('canton')
cantones.head(10)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


cantones.index = [arreglar_cantones(x) for x in cantones.index]
cantones.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


datos_covid.index = [arreglar_cantones(x) for x in datos_covid.canton]
datos_covid.head()

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)


set(cantones.index) - set(datos_covid.index)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

set()


df = cantones.merge(datos_covid,how = "left",
left_index = True,
right_index = True)
df.head(15)


x = df.centroid.x.mean()
print(x)

-83.81587522794443

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.


y = df.centroid.y.mean()
print(y)

9.845582134363136

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  """Entry point for launching an IPython kernel.


import folium

x = df.centroid.x.mean()
y = df.centroid.y.mean()

m = folium.Map(location=[y, x], zoom_start = 9, tiles = None)
folium.TileLayer('CartoDB positron',control=False).add_to(m)

C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  This is separate from the ipykernel package so we can avoid doing imports until
C:\Users\rzamoram\AppData\Local\Continuum\anaconda3\envs\py37ox\lib\site-packages\ipykernel_launcher.py:4: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  after removing the cwd from sys.path.

<folium.raster_layers.TileLayer at 0x1f021967a48>


choropleth = folium.Choropleth(
 geo_data = df,
 data = df,
 columns = ["canton","Vivienda"],
 key_on = "feature.properties.canton",
 fill_color = 'OrRd',
 highlight = True).add_to(m)

m

	name	x	y
22	Banco Nacional	-85.841135	10.299191
43	Banco Nacional	-85.169051	10.823264
55	Banco Nacional	-85.199647	10.672757
76	Banco Nacional	-85.418235	10.057437
77	Banco Nacional	-85.253555	9.993134
88	Banco Nacional	-85.150928	9.628124
93	Banco Nacional	-84.716415	11.032113
97	Banco Nacional	-85.011724	10.897287
103	Banco Nacional	-85.059176	10.728583
104	Banco Nacional	-84.896510	10.544925
117	Banco Nacional	-84.731139	10.092833
123	Banco Nacional	-84.957120	10.280822
126	Banco Nacional	-85.114935	9.958804
150	Banco Nacional	-85.104591	9.687205
159	Banco Nacional	-84.458890	10.466973

	name	x	y
5	Banco Nacional	-85.629489	11.070238
10	Banco Nacional	-85.695239	10.547340
12	Banco Nacional	-85.552203	10.445051
18	Banco Nacional	-85.781695	10.435656
28	Banco Nacional	-85.586820	10.267494
30	Banco Nacional	-85.839514	10.296936
57	Banco Nacional	-85.440634	10.628847
71	Banco Nacional	-85.255454	10.526186
79	Banco Nacional	-85.451839	10.145019
91	Banco Nacional	-85.528888	9.882536
108	Banco Nacional	-84.821709	10.669061
111	Banco Nacional	-85.091362	10.427036
114	Banco Nacional	-84.968444	10.469605
133	Banco Nacional	-84.720780	9.983245
137	Banco Nacional	-84.832643	9.979764

	name	x	y
22	Banco Nacional	-85.841135	10.299191
43	Banco Nacional	-85.169051	10.823264
55	Banco Nacional	-85.199647	10.672757
76	Banco Nacional	-85.418235	10.057437
77	Banco Nacional	-85.253555	9.993134
88	Banco Nacional	-85.150928	9.628124
93	Banco Nacional	-84.716415	11.032113
97	Banco Nacional	-85.011724	10.897287
103	Banco Nacional	-85.059176	10.728583
104	Banco Nacional	-84.896510	10.544925
117	Banco Nacional	-84.731139	10.092833
123	Banco Nacional	-84.957120	10.280822
126	Banco Nacional	-85.114935	9.958804
150	Banco Nacional	-85.104591	9.687205
159	Banco Nacional	-84.458890	10.466973

	cve	canton	Nutrición y Asistencia Médica Básica	Agua y Saneamiento	Vivienda	Seguridad Personal	Acceso a Conocimientos Básicos	Acceso a Información y Comunicaciones	Salud y Bienestar	Sustentabilidad del Ecosistema	...	Rendición de cuentas	Acceso a la cultura y recreación	Inclusión al adulto mayor	Inclusión a población con discapacidad	Inclusión población indígena	Inclusión de migrantes	Inclusión de hogares con jefatura femenina	Población con educación superior	Escolaridad promedio de las mujeres	Población con educación técnica
0	101	SAN JOSE	82.987394	98.665964	63.891581	43.713222	84.284809	73.758822	64.570213	39.810430	...	95.3	20.552	5.252235	7.709731	7.919016	25.562775	36.874519	29.469448	9.733187	4.329589
1	102	ESCAZU	85.931253	98.121264	86.023111	52.939193	88.650664	77.359311	67.819220	64.554111	...	90.0	15.573	6.169883	6.741573	6.495726	10.226506	29.850746	40.279616	10.583268	4.197981
2	103	DESAMPARADOS	88.541844	94.700064	80.789600	58.999818	88.804140	70.986816	68.089101	48.467391	...	33.3	3.071	5.102137	8.366314	9.358289	18.081342	31.065089	21.696907	9.038890	5.288635
3	104	PURISCAL	90.993459	89.766092	90.227325	86.085942	84.829898	58.456934	76.552294	65.577701	...	97.7	5.454	8.805477	6.519700	8.341232	27.045770	17.241379	20.662035	8.512712	7.423228
4	105	TARRAZU	91.495155	96.414943	88.021404	65.438845	77.763379	55.222121	77.395928	71.499005	...	81.0	8.600	4.359313	10.572391	33.012821	25.316456	11.111111	12.510132	7.431191	3.440599
5	106	ASERRI	86.784734	96.168135	80.561890	66.061311	81.685512	64.817405	71.933404	53.966119	...	58.6	2.246	8.748086	10.624700	15.035800	19.402460	32.380952	15.951560	8.207674	4.264233
6	107	MORA	94.646702	97.904214	89.352456	79.862203	88.759700	65.509299	76.397497	57.845085	...	100.0	5.705	7.371255	7.009694	7.415107	12.348285	33.333333	25.396500	9.231101	5.292150
7	108	GOICOECHEA	79.610864	97.117050	81.540361	59.889931	84.789348	75.439587	72.450279	54.076321	...	95.3	9.211	3.743543	7.386839	7.528409	18.536721	44.827586	28.628814	9.704617	4.284503
8	109	SANTA ANA	90.396596	97.623372	85.832592	70.975364	86.128275	76.802068	77.286935	53.389931	...	96.3	13.436	4.861970	6.687831	7.293355	10.380864	35.714286	37.245247	10.364677	4.317240
9	110	ALAJUELITA	93.168844	98.544700	46.213978	54.301052	72.204454	66.581548	74.415128	52.536875	...	86.7	0.387	9.020097	13.531239	13.857678	26.518178	37.401575	13.850704	8.161253	3.350159
10	111	VASQUEZ DE CORONADO	82.283449	91.838378	88.568240	68.306229	83.726808	76.577199	72.162253	62.587511	...	53.3	10.250	3.872730	6.229508	4.628331	7.857143	34.285714	31.075820	9.933610	4.422015
11	112	ACOSTA	93.875730	97.293550	86.457535	96.328282	84.774440	50.580246	77.384992	68.824344	...	40.6	2.474	11.769912	8.275862	10.714286	15.352697	23.529412	11.857351	7.611447	11.082159
12	113	TIBAS	94.036383	99.234036	74.550356	41.264714	75.808156	74.929249	57.225469	51.469446	...	81.7	12.029	3.810577	5.629991	4.623116	23.195649	35.742972	34.699030	10.188252	4.610979
13	114	MORAVIA	96.160704	99.021264	91.392283	70.452464	90.366621	79.269724	73.507914	61.066812	...	94.3	13.352	3.259098	5.356545	7.284768	8.231972	16.129032	40.004579	10.807282	4.478757
14	115	MONTES DE OCA	94.328260	90.410728	93.709855	20.158451	74.780648	82.424025	69.421412	57.335312	...	75.3	28.291	2.073171	3.572090	3.030303	8.791028	23.809524	51.987624	11.828741	4.365419

	cve	canton	oportunidades	ips
0	101	SAN JOSE	Nutrición y Asistencia Médica Básica	82.987394
1	102	ESCAZU	Nutrición y Asistencia Médica Básica	85.931253
2	103	DESAMPARADOS	Nutrición y Asistencia Médica Básica	88.541844
3	104	PURISCAL	Nutrición y Asistencia Médica Básica	90.993459
4	105	TARRAZU	Nutrición y Asistencia Médica Básica	91.495155
5	106	ASERRI	Nutrición y Asistencia Médica Básica	86.784734
6	107	MORA	Nutrición y Asistencia Médica Básica	94.646702
7	108	GOICOECHEA	Nutrición y Asistencia Médica Básica	79.610864
8	109	SANTA ANA	Nutrición y Asistencia Médica Básica	90.396596
9	110	ALAJUELITA	Nutrición y Asistencia Médica Básica	93.168844

Tarea 3¶

Ricardo Zamora Mennigke¶

Visualizacion¶

	provincia	canton	poblacion	area_k2	geometry
0	Puntarenas	Corredores	51291.0	623.723527	POLYGON ((-82.90137 8.72708, -82.90033 8.72265...
1	Puntarenas	Golfito	44572.0	1750.056183	MULTIPOLYGON (((-83.46660 8.68827, -83.46669 8...
2	Puntarenas	Coto Brus	44176.0	944.175405	POLYGON ((-82.96647 9.09421, -82.96337 9.09420...
3	Puntarenas	Osa	30818.0	1922.774483	POLYGON ((-83.83946 9.25534, -83.83642 9.25533...
4	Puntarenas	Buenos Aires	52126.0	2382.972927	POLYGON ((-83.32101 9.38409, -83.31462 9.38327...

	provincia	poblacion	area_k2	geometry	cve	canton	oportunidades	ips
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Nutrición y Asistencia Médica Básica	85.280540
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Agua y Saneamiento	95.038378
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Vivienda	69.104107
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Seguridad Personal	87.244399
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Acceso a Conocimientos Básicos	83.601755
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Acceso a Información y Comunicaciones	50.593854
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Salud y Bienestar	70.678446
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Sustentabilidad del Ecosistema	56.886927
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Derechos Personales	76.330000
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Libertad Personal y de Elección	78.121495
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Tolerancia e Inclusión	78.881617
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Acceso a Educación Superior	37.934010
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Necesidades Humanas Básicas	84.166856
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	Fundamentos del Bienestar	65.440245
ABANGARES	Guanacaste	19733.0	646.178946	POLYGON ((-84.91642 10.38545, -84.91500 10.384...	507.0	ABANGARES	oportunidades	67.816781

	provincia	canton	poblacion	area_k2	geometry
18	Cartago	El Guarco	45548.0	171.573039	POLYGON ((-83.93649 9.85420, -83.92932 9.85254...
19	Cartago	Cartago	161727.0	278.997036	POLYGON ((-83.86737 9.97095, -83.86892 9.96971...
21	Cartago	Paraíso	62007.0	477.139035	POLYGON ((-83.77791 9.89517, -83.77752 9.89362...
22	Cartago	Jiménez	16255.0	250.075984	POLYGON ((-83.76414 9.94766, -83.75970 9.94653...
23	Cartago	Turrialba	73616.0	1589.335834	POLYGON ((-83.81609 10.08361, -83.72326 10.039...

	provincia	poblacion	area_k2	geometry	cve	canton	oportunidades	ips
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Nutrición y Asistencia Médica Básica	92.760577
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Agua y Saneamiento	97.978736
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Vivienda	89.356684
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Seguridad Personal	69.972781
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Acceso a Conocimientos Básicos	88.816013
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Acceso a Información y Comunicaciones	54.923713
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Salud y Bienestar	80.897354
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Sustentabilidad del Ecosistema	67.803337
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Derechos Personales	79.770000
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Libertad Personal y de Elección	79.237891
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Tolerancia e Inclusión	79.774300
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Acceso a Educación Superior	36.487360
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Necesidades Humanas Básicas	87.517195
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	Fundamentos del Bienestar	73.110104
ALVARADO	Cartago	15219.0	79.140674	POLYGON ((-83.81336 10.01513, -83.81288 10.014...	306	ALVARADO	oportunidades	68.817388

	provincia	canton	poblacion	area_k2	geometry	indice
0	Puntarenas	CORREDORES	51291.0	623.723527	POLYGON ((-82.90137 8.72708, -82.90033 8.72265...	1
1	Puntarenas	GOLFITO	44572.0	1750.056183	MULTIPOLYGON (((-83.46660 8.68827, -83.46669 8...	1
2	Puntarenas	COTO BRUS	44176.0	944.175405	POLYGON ((-82.96647 9.09421, -82.96337 9.09420...	1
3	Puntarenas	OSA	30818.0	1922.774483	POLYGON ((-83.83946 9.25534, -83.83642 9.25533...	1
4	Puntarenas	BUENOS AIRES	52126.0	2382.972927	POLYGON ((-83.32101 9.38409, -83.31462 9.38327...	1
5	San José	PEREZ ZELEDON	142789.0	1901.393446	POLYGON ((-83.77329 9.59825, -83.77217 9.59826...	1
6	Puntarenas	QUEPOS	32121.0	559.010331	POLYGON ((-84.13572 9.57168, -84.13337 9.57091...	1
7	Limón	TALAMANCA	41518.0	2814.658267	POLYGON ((-82.89452 9.76752, -82.89216 9.76713...	1
8	Puntarenas	PARRITA	19457.0	479.629981	POLYGON ((-84.30298 9.64969, -84.30067 9.64754...	1
9	San José	TARRAZU	18264.0	290.111618	POLYGON ((-83.98178 9.71802, -83.97882 9.71819...	1
10	San José	DOTA	7846.0	405.833655	POLYGON ((-83.98595 9.73927, -83.98254 9.73711...	1
11	Puntarenas	GARABITO	24737.0	315.381452	POLYGON ((-84.67583 9.87729, -84.67448 9.87743...	1
12	San José	LEON CORTES CASTRO	13493.0	121.938260	POLYGON ((-84.09415 9.74942, -84.09264 9.74917...	1
13	San José	PURISCAL	37345.0	554.985169	POLYGON ((-84.40184 9.90958, -84.40088 9.90939...	1
14	San José	ASERRI	62477.0	168.425499	POLYGON ((-84.08014 9.87557, -84.07916 9.87509...	1